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Build and query Kusto graphs from natural language. Covers transient graphs (make-graph), persistent graph models/snapshots, pattern matching (graph-match), shortest paths, connected components, and graph-to-table export. Generates the edges-first thinking: define edges, define node lookups, union, make-graph. WHEN: make-graph, graph-match, graph-shortest-paths, graph-to-table, graph-mark-components, persistent graph, graph model, graph snapshot, build a graph from data, find paths between nodes, pattern matching in graph, connected components, transient graph, Kusto graph, KQL graph.

日本語の概要は準備中です。原文の説明を表示しています。

Plan, deploy, operate, and troubleshoot multi-rack (rack scale) deployments of Azure Local — preintegrated racks scaling to hundreds of machines, built on Network Fabric Controller, Cluster Manager, SAN storage, and managed network fabric. Use for the Microsoft.NetworkCloud and Microsoft.ManagedNetworkFabric control plane. NOT for standard 1-16 node Azure Local, and NOT for rack-aware clusters (two racks as availability zones, up to 8 nodes, synchronous replication) — those are standard scale. WHEN: multi-rack, rack scale Azure Local, aggregation rack, compute rack, Network Fabric Controller, NFC, Cluster Manager, network fabric, isolation domain, az networkcloud, az networkfabric, multi-rack logical network, multi-rack Arc VM.

日本語の概要は準備中です。原文の説明を表示しています。

Compose IRQL (Incident Response Query Language) queries for Kusto cybersecurity investigations. Translates natural language hunting questions into composable IRQL pipelines using Get_*, Extract_*, and Enrich_* functions. WHEN: IRQL query, security hunt, threat hunting KQL, incident response query, compose hunting pipeline, failed logins, phishing investigation, lateral movement, process execution, file creation events.

日本語の概要は準備中です。原文の説明を表示しています。

Assess whether source code is ready to deploy to Azure — the check BEFORE infrastructure work. Evaluates build health, app completeness, dependencies and local services, stack compatibility, and deployment feasibility. Answers questions about what your app needs before it can be deployed — frameworks, dependencies, and configuration. Checks whether dependencies are compatible and identifies deployment blockers and unsupported frameworks. WHEN: "evaluate my repo", "is my app ready to deploy", "what does my app need to deploy", "what do I need before deploying", "does my app need", "can I ship this to Azure", "scan my repo for issues", "is this app deployable", "check if my app is ready for Azure", "do I need a Dockerfile", "what's blocking my deployment", "are there any blockers", "are my dependencies compatible", "does Azure support my framework", "what needs to change before deploying", "check my app configuration".

日本語の概要は準備中です。原文の説明を表示しています。

Debug Azure production issues on Azure using AppLens, Azure Monitor, resource health, and safe triage. WHEN: debug production issues, troubleshoot app service, app service high CPU, app service deployment failure, troubleshoot container apps, container app 503 or target port mismatch, troubleshoot functions, function telemetry missing or stopped after a config/connection-string change, troubleshoot AKS, VM RDP, Linux SSH, VM black screen, can't connect to VM, reset VM password, NSG or firewall blocking, kubectl cannot connect, kube-system/CoreDNS failures, pod pending, crashloop, node not ready, upgrade failures, analyze logs, KQL, insights, image pull failures, cold start issues, health probe failures, resource health, root cause of errors, troubleshoot event hubs, troubleshoot service bus, messaging SDK error, AMQP connection failure, message lock lost, lock renewal during long-running processing, service bus dead letter.

日本語の概要は準備中です。原文の説明を表示しています。

Foundry IQ knowledge bases. WHEN: make local or Blob documents searchable; create/diagnose KBs; triage unsupported connectors or multi-source KB creation/reconfiguration; connect existing KB to agents (including multi-source KBs); create/reuse a Search service; retrieve from an existing knowledge base with citations; no brand words needed. Read its procedure before query/target questions. NOT: other KB providers, repository-file search, classic Azure AI Search index/query/app work, generic agent creation.

日本語の概要は準備中です。原文の説明を表示しています。

Deploy Python (Flask/Django/FastAPI) code to Azure App Service Linux. WHEN: "Flask App Service", "Django App Service", "FastAPI App Service", "deploy Python to App Service". DO NOT USE FOR: Container Apps, Functions, non-Python, Terraform/Bicep/IaC, full infra — use azure-prepare.

日本語の概要は準備中です。原文の説明を表示しています。

Assess and upgrade Azure workloads between plans, tiers, or SKUs, or modernize Azure SDK dependencies in source code. WHEN: upgrade Consumption to Flex Consumption, upgrade Azure Functions plan, change hosting plan, function app SKU, migrate App Service to Container Apps, modernize legacy Azure Java SDKs (com.microsoft.azure to com.azure), migrate Azure Cache for Redis (ACR/ACRE) to Azure Managed Redis (AMR).

日本語の概要は準備中です。原文の説明を表示しています。

Create a qualitative risk register and mitigation plan using a Probability x Impact matrix. Use when a project needs structured risk identification, scoring, ownership, and response planning.

日本語の概要は準備中です。原文の説明を表示しています。

Run a structured Azure incident response workflow for triage, diagnosis, mitigation, and root cause analysis. Use when operations or security teams need guided incident handling for Azure service symptoms.

日本語の概要は準備中です。原文の説明を表示しています。

Build, refresh, report, or probe an accessibility coverage matrix across criteria, surfaces, and evidence methods. Use when assessing coverage with the accessibility runtime harness and generated evidence bundle.

日本語の概要は準備中です。原文の説明を表示しています。

Export Design Thinking artifacts to a FigJam board or Figma Design file through the Figma MCP server. Use when a team wants collaborative visual review of Method 1, 3, 4, 5, or 6 artifacts, or accepts a DT Coach board-export offer.

日本語の概要は準備中です。原文の説明を表示しています。

Run one independent Council critique against engagement-report research evidence. Use as the manual separate-session fallback when independent critic agents are unavailable.

日本語の概要は準備中です。原文の説明を表示しています。

Stage user-selected paths, confirm the exact staged set, and create one local Conventional Commit, or generate a commit message for staged changes without committing. Use when you want a guarded commit or a ready-to-paste message.

日本語の概要は準備中です。原文の説明を表示しています。

Coordinate Git merge, rebase, and rebase --onto workflows with conflict resolution, optional review pauses, and a completion summary. Use when integrating a branch locally and resolving conflicts without pushing.

日本語の概要は準備中です。原文の説明を表示しています。

Create or update project cspell configuration by resolving the loaded config, active dictionaries, curated words, ignore paths, and validation evidence. Use when spell-check configuration needs project words or ignores.

日本語の概要は準備中です。原文の説明を表示しています。

Generate synthetic datasets in a Jupyter notebook after the dataops synthetic-data preflight passes. Use when creating new synthetic data or preparing a guarded local replacement candidate from an approved source.

日本語の概要は準備中です。原文の説明を表示しています。

Audit Git configuration with one read-only baseline command, then propose confirmed, non-destructive fixes for identity, editor, and diff and merge tooling, with signing and safe.directory help only on request. Use when setting up or checking Git on a workstation.

日本語の概要は準備中です。原文の説明を表示しています。

Consolidated Responsible AI standards reference: NIST AI RMF 1.0, AI STRIDE threat-modeling overlay, EU AI Act risk tiers, and an open-standards catalog with phase mapping

日本語の概要は準備中です。原文の説明を表示しています。

Shared work-item templates and conventions for ADO and GitHub backlog handoff across the RAI, Security, SSSC, Accessibility, and Privacy planners

日本語の概要は準備中です。原文の説明を表示しています。

On-demand RAI planner reference pack covering Phase 1 capture, Phase 2 risk classification and the optional Mural board bootstrap, Phase 5 impact assessment, and Phase 6 review and backlog handoff.

日本語の概要は準備中です。原文の説明を表示しています。

OWASP Docker Top 6 knowledge base for identifying, assessing, and remediating Docker container security risks.

日本語の概要は準備中です。原文の説明を表示しています。

OWASP Agentic Security Top 10 knowledge base for identifying, assessing, and remediating AI agent system security risks.

日本語の概要は準備中です。原文の説明を表示しています。

Independently assess an RPI plan without editing it. Use when an implementation-ready plan needs a credibility check or a revised plan needs its earlier findings reconciled.

日本語の概要は準備中です。原文の説明を表示しています。